SKILL COVERED
Programming. pandas. NumPy.
PRE REQUISTIES
No Prior Programming experience required
NEW BATCH STARTS
08 September 2018
DURATION
6 Months
Why learn MATLAB to simulate data?
Matlab in not only a programming language, but a programming environment as well. You can perform operations from the command line, as a sophisticated calculator.Or you can create programs and functions that perform repetitive tasks, just as any other computer language.
This course is not a MATLAB tutorial. It is an introductory programming course that uses MATLAB to illustrate general concepts in computer science and programming. Students who successfully complete this course will become familiar with deep concepts in MATLAB
Effective & Engaging Content
Get started with programming through interactive content like quizzes, videos, and hands-on projects. Our learn-by-doing approach is the most effective way to learn to code.
Beneficial and Supportive Project Review
Advance quickly and successfully through the curriculum with the support of expert reviewers whose detailed feedback will ensure you master all the right skills.
What You Will Learn?
Master MATLAB Programming fundamentals and Simulink to increase your number crunching abilities. Learn MATLAB and Simulink Programming is a course that focuses on teaching students about the various commands, functions, and features that MATLAB and Simulink have to offer.Data and data flow in MATLAB
Matrix Operations & Operators
Reshaping Matrices
Importing Exporting Of Data
Arrays
Data types
File Input-Output
Communication with external devices
Editing and debugging M Files
Writing script files
writing functions
Error Correction
M-Lint Automatic Code Analyzer
Saving files
Programming
Flow control
Conditional Statements
Error Handling
Work with multidimensional array
Cell Array & Characters
Developing user defined function
Scripts and other Functions
Basic Technical Level Computing with MATLAB
MATLAB Graphics
Simple graphics
Graphic Types
Plotting functions
Creating plot &Editing plot (2D and 3D)
Graphics Handles
GUI (Graphical User Interface)
Simulink
Introduction
Importance
Model Based Design
Tools
Mathematical Modeling
Converting Mathematical Model into Simulink Model
Running Simulink Models
Importing Exporting Data
Solver Configuration
Masking Block/Model
Basic Technical Level Computing with MATLAB
Control System Toolbox
General instructions
Create linear models
Classes of Control System Toolbox
Discussion on state space representation
Transfer function
System gain and dynamics
Time & Frequency domain analysis
Classical design, State Space Model
Transfer function representation, System response
LTI viewer detail and explanation about LTI viewer
Designing of compensator
Use of SISO design
Signal Processing Toolbox
Basics of Signal Processing
Representing Signals
Analysis of different Signals
Complex Signals
Filter Designing
Using the Filter Designing GUIs
Analyzing the filter plots
Filter Designing using Script Files
Speech Recording
Speech Processing
Other Signal Processing FunctionsB
Communication Toolbox
Signal Sources
BER Tool
Modulation
Special Filter
Channels
Equalizers
Image Processing Toolbox
Signal Sources
BER Tool
Modulation
Special Filter
Channels
Equalizers
Communication Toolbox
Reading and Writing Image Data
Displaying and Exploring Image
Spatial Transformation
Image Registration
Designing and implementing 2D linear Filters for Image Data
Morphological Operations
Transforms
Analyzing and Enhancing Images
ROI based Processing
Neighborhood and Block operations
Computer Vision Systems Toolbox
Input, Output, and Conversions
Display and Graphics
Registration and Stereo Vision
Motion Estimation and Tracking
Geometric Transformations
Filters, Transforms, and Enhancements
Fuzzy Logic Toolbox
Basic introduction to fuzzy logic
Fuzzy Versus Non-fuzzy Logic
Foundations of Fuzzy Logic
Fuzzy Inference Systems
Building Systems with Fuzzy Logic Toolbox Software
Building Fuzzy Inference Systems Using Custom Functions
Working from the Command Line
Working in Simulink Environment
Simulating Fuzzy Inference Systems Using the Fuzzy Inference Engine
Neural Network Toolbox
Network Objects, Data, and Training Styles
Multilayer Networks and Backpropagation Training
Control Systems
Radial Basis Networks
Self-Organizing and Learning
Vector Quantization Nets
Adaptive Filters and Adaptive Training
Stateflow in Simulink
Stateflow Chart Concepts
Stateflow Chart Notation
Stateflow Chart Semantics
Building Mealy and Moore Charts
Using Actions in Stateflow Charts
Stateflow Design Patterns
Truth Table Functions for Decision-Making Logic
Using Simulink Functions in Stateflow Charts
Debugging and Testing Stateflow Charts
Exploring and Modifying Charts
Semantic Rules Summary
Semantic Examples
Analysis of C MEX files
C/C++ Source MEX-Files
Examples of C/C++ Source MEX-Files
Debugging C/C++ Language MEX-Files
Handling Large mxArrays
Memory Management
Large File I/O
Fuzzy Logic Toolbox
Basic introduction to fuzzy logic
Fuzzy Versus Non-fuzzy Logic
Foundations of Fuzzy Logic
Fuzzy Inference Systems
Building Systems with Fuzzy Logic Toolbox Software
Building Fuzzy Inference Systems Using Custom Functions
Working from the Command Line
Working in Simulink Environment
Simulating Fuzzy Inference Systems Using the Fuzzy Inference Engine
Students from Colleges
Our students are students as well as working professionals. Colleges' students take interest in learning such emerging technologies.
